Research Progress of Ultrasound Radiomics in Predicting Axillary Lymph Node Metastasis of Breast Cancer
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摘要: 乳腺癌已成为全球女性发病率最高的恶性肿瘤,是全球广泛关注的重点疾病。乳腺癌腋窝淋巴结转移的术前准确评估对于手术治疗决策至关重要,而传统的腋窝超声对少量和微转移淋巴结识别困难,无法满足精准治疗需求。近年来,随着人工智能和影像学技术的快速发展,影像组学方法可提取人眼难以识别的深层次图像信息,在医学影像领域得到了广泛应用。本文介绍超声影像组学术前预测乳腺癌淋巴结转移的研究进展,并对该领域的未来发展进行展望。Abstract: Breast cancer, as the most common malignant tumor in women worldwide, has become the focus of global attention. Axillary lymph node tumor burden is an important prognostic indicator of it. Ultrasound is the most commonly used imaging method, but its sensitivity is not high, especially for the diagnosis of small and micro lymph node metastasis. In recent years, the emerging Radiomics in machine learning field has been widely used in the field of medical imaging. Because it can extract high-level information of images that is difficult to be recognized by human eyes, it has been used to establish clinical prediction models. This paper introduced the value of preoperative sonography, sketched Radiomics, and summarized the research progress of this method in predicting lymph node metastasis of breast cancer. This new method is expected to provide a reliable basis for individualized and accurate diagnosis and treatment of breast cancer.
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Key words:
- breast cancer /
- axillary lymph node metastasis /
- radiomics /
- deep learning /
- ultrasonography
作者贡献:高远菁负责文献检索、数据分析及论文初稿撰写; 朱庆莉负责论文初稿修订; 姜玉新负责论文审校。利益冲突:无 -
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